AP Statistics Chapter 12: Surveys

Population

The entire group of individuals or instances about whom we hope to learn.

Sample

A (representative) subset of a population, examined in hope of learning about the population.

Sample Survey

A study that asks questions of a sample drawn from some population in the hope of learning something about the entire population

Bias

A systematic failure of a sampling method to represent its population is bias. It is almost impossible to recover from bias, so effort to avoid it are well spent. Common errors include

- Relying on voluntary response.

- Under-coverage of the population.

- Nonresponse bias.

- Response bias.

Randomization

the best defense against bias, in which each individual is given a fair, random chance of selection

Matching

Any attempt to force a sample to resemble specified attributes of the population

Sample Size

the number of individuals in a sample; determines how well the sample represents the population, not the fraction of the population sampled.

Census

population count.

Population parameter

a numerically valued attribute of a model for a population.

Statistic, sample statistic

values calculated for sampled data. Those that correspond to, and thus estimate, a population parameter, are of particular interest. For example, the mean income of all employed people in a representative sample can provide a good estimate of the corresponding population parameter. The term "sample statistic" is sometimes used, usually to parallel the corresponding term, "population parameter."

representative

this kind of sample accurately reproduces the characteristics of the population a researcher is studying

Simple random sample (SRS)

process of taking a sample n in which each set of n elements in the population has an equal chance of selection.

Sampling frame

the individuals or clusters of individuals who might actually be selected for inclusion in the sample

sampling variability

the natural tendency of randomly drawn samples to differ, one from another; the natural result of random sampling.

Stratified random sample

A sampling design in which the population is divided into several subpopulations, or strata, and random samples are then drawn from each stratum.

Cluster Sample

a sampling design in which entire groups are chosen at random. Usually selected as a matter of convenience, practicality or cost. each cluster should be diverse in character and representative of the population, so all the groups should be similar to each other

Multistage sample

sampling schemes that combine several sampling methods

Systematic sample

a sample drawn by selecting individuals systematically from a sampling frame

Voluntary response bias

bias introduced to a sample when individuals can choose on their own whether to participate in the sample

Convenience sample

sample consisting of the individuals who are conveniently available.

Undercoverage

A sampling scheme that biases the sample in a way that gives a part of the population less representation than it has in the population.

Nonresponse bias

Bias introduced to a sample when a large fraction of those sampled fails to respond. Those who do respond are likely to not represent the entire sample. Voluntary response bias is a one form. For example, those who are at work during the day won't respond to a telephone survey conducted only during working hours.

Response bias

Anything in a survey design that influence response. Typically arises from the wording of questions, which may suggest a favored response. Voters, for example, are more likely to express support of "the president" than support of the particular person holding that office at the moment.